Following the light Novel event reconstruction techniques for neutrino oscillation analyses in KM3NeT/ORCA

Neutrinos are tiny, subatomic particles which currently present some outstanding questions in the field of particle physics. Though neutrino oscillations are now an understood phenomenon, efforts are still underway to measure the neutrino oscillation parameters even more precisely. Furthermore, the ordering of the three neutrino mass states relative to one another - the neutrino mass ordering - is still unknown. The KM3NeT/ORCA detector is currently being built in the Mediterranean Sea to address such questions. This infrastructure surrounds huge volumes of seawater with photodetectors, bypassing the tiny interaction cross section of these particles, and detecting the Cherenkov radiation of products of neutrino interactions in the water.
In this thesis, the software used to simulate atmospheric muons in the detector using parametric formulae is tuned to KM3NeT/ORCA data, resulting in an improved simulation of the atmospheric muons, which form the main background for neutrino analyses. A novel neutrino event reconstruction algorithm is developed and explored in this thesis, aiming to reconstruct neutrino events with both a track-like and particle shower-like component. The estimate of the reconstructed neutrino energy is improved upon with this technique, as well as directly reconstructing the fractional energy transfer to the hadronic shower component of the interaction. This reconstruction technique also shows the potential for identifying different neutrino interaction channels. The improved energy estimate and the potential to identify the interaction channel pave the way for future analyses, leading to an improved measurement of the neutrino oscillation parameters and determination of the yet-unknown neutrino mass ordering.